Scientists at the University of Manchester will link together the ARM chips as the system architecture of a massive computer, dubbed SpiNNaker, or Spiking Neural Network architecture.

Despite the mass of chips it will only be possible to recreate models of up to one percent of the human brain.

The chips have arrived and are past functionality testing.

A similar experiment was once attempted with a load of old Centrino chips found at the back of our stationary cupboard, though so far we haven’t even managed to replicate the cranial workings of a particularly slow slug.

The work, headed up by Professor Steve Furber, has the potential to become a revolutionary tool for neuroscientists and psychologists in understanding how our brains work.

SpiNNaker will attempt to replicate the workings of the 100 billion neurons and the 1,000 million connections that are used to create high connectivity in cells.

SpiNNaker will model the electric signals that neurons emit, with each impulse modelled as a ‘packet’ of data, similar to the way that information is transferred over the internet.

The packet is sent to other neurons, represented by small equations solved in real time by ARM processors.

The chips, designed in Machester and built in Taiwan, each contain 18 ARM processors.

The bespoke 18 core chips are able to provide the computing power of a personal computer in a fraction of the space, using just one watt of power.

Now that the chips have arrived it will be possible to get cracking on building model.

“The project revolves around getting the chips made, which has taken the past five years to get right,” Professor Steve Furber told TechEye.

“We will know be increasing the scale of the project over the next 18 months before it reaches its final form, with one million processors used. We already have the system working on a smaller scale, and we are able to look at fifty to sixty thousand neurons currently.”

As well as offering possibilities as a scientific research tool, Furber hopes that the system will help pave the way for computational advancements too.

“It will help to analyse the intermediate levels of the brain, which are very difficult to focus on otherwise,” he says.

“Another area which this help is in building more reliable computing systems. As chip manufacturers continue towards the end of Moore’s Law, transistors will become increasingly unreliable. And computer systems are very susceptible to malfunctioning transistors.”

Furber says biology works differently. “Biology, on the other hand, reacts to the malfunctioning of neurons very well, with it happening regularly with all brains, so this could help future chips become more reliable.”

Of course, we also wanted to know how this all compares with Intel’s famous bumblebee claims.

Unfortunately, professor Furber couldn’t specifically help us with information about bumblebee brain processing.

He was, however, able to reel off some details about the honeybee.

“The honeybee brain has around 850,000 neurons so we will be able to reach that level of processing in the next few months. Of course, we don’t have a honeybee brain model to run, but we will have the computing power.”